Sentiment Analysis of Tweets {https://t.co/oUo7oEPJOc} #rstats #DataScience
— R-bloggers (@Rbloggers) April 4, 2022
Basics of Text Mining in R {https://t.co/14MYZXbGiB} #rstats #DataScience
— R-bloggers (@Rbloggers) April 1, 2022
R Shiny in Government – Top 7 Dashboards You Should See {https://t.co/K9B5t5rUyM} #rstats #DataScience
— R-bloggers (@Rbloggers) April 5, 2022
New features in R 4.2.0 {https://t.co/ei9WWffEyB} #rstats #DataScience
— R-bloggers (@Rbloggers) April 1, 2022
Dual axis charts in ggplot2 – how to make them and why they can be useful {https://t.co/EorkOeHu04} #rstats #DataScience
— R-bloggers (@Rbloggers) April 7, 2022
R Access to Twitter’s V2 API {https://t.co/QRUTAwVaC8} #rstats #DataScience
— R-bloggers (@Rbloggers) April 5, 2022
How to make a boxplot in R {https://t.co/6NoIQU7Aap} #rstats #DataScience
— R-bloggers (@Rbloggers) April 6, 2022
Why mean substition is a bad idea, almost always {https://t.co/8UJw697tHP} #rstats #DataScience
— R-bloggers (@Rbloggers) April 4, 2022
Next — Today I Learnt About R {https://t.co/DufTwoSsTw} #rstats #DataScience
— R-bloggers (@Rbloggers) April 2, 2022
Notes on Github {https://t.co/dhCfpjWmRV} #rstats #DataScience
— R-bloggers (@Rbloggers) April 1, 2022
Greatly Revised Edition of Tidyverse Skeptic {https://t.co/OiSdSKgHSD} #rstats #DataScience
— R-bloggers (@Rbloggers) April 3, 2022
DuckDB: Quacking SQL {https://t.co/wEfp0wvwFY} #rstats #DataScience
— R-bloggers (@Rbloggers) April 2, 2022
Sentiment Analysis of Tweets {https://t.co/oUo7oEPJOc} #rstats #DataScience
— R-bloggers (@Rbloggers) April 4, 2022
Monte Carlo Analysis in R {https://t.co/X5J5EgA3u4} #rstats #DataScience
— R-bloggers (@Rbloggers) March 12, 2022
Classification: Logistic Regression and Random Forest {https://t.co/i18v8RedYE} #rstats #DataScience
— R-bloggers (@Rbloggers) March 31, 2022
Markov Chain Introduction in R {https://t.co/M4iyIbjj62} #rstats #DataScience
— R-bloggers (@Rbloggers) March 13, 2022
R Shiny in Life Sciences – Top 7 Dashboard Examples {https://t.co/iNZgHjyP7K} #rstats #DataScience
— R-bloggers (@Rbloggers) March 29, 2022
How to Use R and Python Together? Try These 2 Packages {https://t.co/bBnt7pG52N} #rstats #DataScience
— R-bloggers (@Rbloggers) March 22, 2022
Dual axis charts – how to make them and why they can be useful {https://t.co/xxw2uwEMvo} #rstats #DataScience
— R-bloggers (@Rbloggers) March 14, 2022
Basics of Text Mining in R {https://t.co/14MYZXbGiB} #rstats #DataScience
— R-bloggers (@Rbloggers) April 1, 2022
Predictive Analytics Models in R {https://t.co/XlkJAaLryA} #rstats #DataScience
— R-bloggers (@Rbloggers) March 13, 2022
Understanding the native R pipe |> {https://t.co/rOPUrHbmtR} #rstats #DataScience
— R-bloggers (@Rbloggers) March 15, 2022
Dashboards in R Shiny {https://t.co/BbirS9zEnj} #rstats #DataScience
— R-bloggers (@Rbloggers) March 15, 2022
R Shiny in Government – Top 7 Dashboards You Should See {https://t.co/K9B5t5rUyM} #rstats #DataScience
— R-bloggers (@Rbloggers) April 5, 2022
---
title: "RBloggers Top Tweets"
output:
flexdashboard::flex_dashboard:
vertical_layout: scroll
source_code: embed
theme:
version: 4
bootswatch: yeti
css: styles/main.css
---
```{r setup, include=FALSE}
library(flexdashboard)
library(dplyr)
library(httr)
library(lubridate)
library(jsonlite)
library(purrr)
rbloggers <- fromJSON("data/rbloggers.json")
get_tweet_embed <- function(user, status_id) {
url <-
stringr::str_glue(
"https://publish.twitter.com/oembed?url=https://twitter.com/{user}/status/{status_id}&partner=&hide_thread=false"
)
response <- GET(url) %>%
content()
return(shiny::HTML(response$html))
}
```
Column {.tabset .tabset-fade}
-----------------------------------------------------------------------
### Top Tweets - 7 days {.tweet-wall}
```{r}
rblog_7 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 7, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_7_html <-
map2_chr(rblog_7$screen_name, rblog_7$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_7_html}"))
```
### Top Tweets - 30 days {.tweet-wall}
```{r}
rblog_30 <- rbloggers %>%
mutate(created_at = as_date(created_at)) %>%
filter(created_at %within% interval(start = today() - 30, end = today())) %>%
slice_max(favorite_count + retweet_count, n = 12)
rblog_30_html <-
map2_chr(rblog_30$screen_name, rblog_30$status_id, get_tweet_embed)
shiny::HTML(stringr::str_glue("{rblog_30_html}"))
```